At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Job Summary Nielsen is a leading online, radio and television research company specializing in industry leading measurement solutions that provide clients with a comprehensive understanding of the online world. Our Data Science team is experimenting, testing, and driving major insights that impact both a global network of clients and own Nielsen direction. As a Data Scientist you will be responsible for high-quality design, execution and delivery of global analytics solutions, performance dashboards, and analytical studies. Excited? Come join us! This role is based out of Mumbai ,is a part of GCM team and will be reporting to GCM regional team leader. To leverage extensive data science expertise in driving the development and refinement of advanced analytical models that enhance Nielsen's audience measurement products for clients. To build and build custom data pipeline for clients within Nielsen’s proprietary audience measurement tool - NielsenOne. The role involves translating complex datasets into actionable insights, leading cross-functional projects, and contributing to the strategic direction of the analytics function.
Responsibilities
Drive the development of advanced analytics to improve predictive modeling and real-time insights for Nielsen's data products.
Craft scalable, interpretable models, employing AI and machine learning to enhance data product sophistication and solve customer problems quickly.
Harness diverse datasets to engineer features that bolster predictive capabilities, optimizing Nielsen's data analysis processes.
Articulate complex analytics methodologies to internal and external Nielsen stakeholders, demonstrating their direct relevance to strategic audience measurement goals.
Champion data-driven cultures within Nielsen, spotlighting the role of sophisticated data analysis in resolving audience measurement challenges for enhanced client impact.
Direct educational initiatives at Nielsen to heighten the application of data science in audience analytics, aligning with the latest industry trends and standards.
Provide expert apprenticeship to Nielsen's data science team, cultivating advanced skill sets in audience measurement analytics.
Lead effective cross-functional collaboration between data science and technology to advance the analytical tools and applications used in audience analytics and convert methodologies into client impact.
Stay informed about the latest technology and methodology by participating in industry forums, having an active peer network.
Cultivate a team environment focused on continuous learning, where innovative audience measurement methodologies are developed and refined through collaborative effort.
Key Skills
Possession of a Bachelor’s degree, with a preference for an MS or PhD in Data Science, Computer Science, Engineering, or Statistics.
At least 5 years of experience in data science roles, or a graduate degree in a quantitative discipline with a demonstrated skill set in data science and 2+ years of work experience.
Experience in media industry /content management is good to have.
Proven ability to merge and transform diverse internal and external datasets to create innovative features.
Expertise in using machine learning for clustering, classification, regression, anomaly detection, and simulation problems, particularly with large datasets.
High proficiency in Python, R, SQL, and PySpark; experience with ETL (e.g., Airflow) and cloud-based environments (e.g., AWS) is a plus.
Familiarity with big data technologies like Hadoop, Spark, H20.ai, cloud AI platforms, and containerization; proficiency with DevOps tools.
Experience in using data visualization tools such as Tableau, R Shiny, Plotly, etc., for effective communication of complex data insights.
Deeper knowledge of handling big data environments and understanding of data engineering principles.
Exceptional communication and collaboration skills to understand and cater to business partner needs and work effectively in team settings.
A customer-first approach by anchoring and solving customer problems rapidly, aligning data-driven decisions with customer needs to deliver rapid customer impact.
A bias for action and an ability to deliver outstanding results through effective task prioritization and time management.
